Rapid Estimation of Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) Composition Using ATR-FTIR.

Polymers(2023)

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摘要
A great research effort is involved in polyhydroxyalkanoates (PHAs) production and characterization since they are an attractive degradable polyester family that potentially could substitute oil-based polymers. This is due to two main key factors: their production is sustainable, being that they are produced by microorganisms possibly fed by organic waste-derived products, and they are degradable. Moreover, PHAs' thermal and mechanical properties could be tuned by varying their monomeric composition through the proper selection of microorganism feedstock and bioreactor operative conditions. Hence, a rapid and facile determination of the PHA chemical structure by widely available instrumentation is useful. As an alternative to the standard gas-chromatographic method, a new procedure for the composition determination of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (P3HBV), the most common PHA copolymer, by attenuated total reflection FTIR (ATR-FTIR) is presented. It is based on the linear dependence of selected and normalized absorption band intensity with the molar fraction of repeating units. To break free from the crystallinity variability, which affects the result reproducibility and data scattering, the polymer sample was rapidly quenched from the melt directly on the surface of the ATR internal reflection element and analyzed. The data obtained from 14 samples with a molar fraction of 3-hydroxybutyrate repeating units () ranging from 0.15 to 1 were analyzed. According to preliminary analyses, the normalized intensity of two absorption bands was selected to develop a calibration method able to predict of unknown samples and to evaluate the related uncertainty through prediction intervals of inverse regression. The proposed method proves to be useful for an easy and rapid estimation of P3HBV composition.
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poly(3-hydroxybutyrate-co-3-hydroxyvalerate),attenuated total reflection FTIR,composition determination,inverse linear regression
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